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检索条件"任意字段=Workshop on Parallel and Distributed Real-Time Systems"

共 7655 条记录，以下是1401-1410 订阅

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A parallel Uncertain Frequent Itemset Mining Algorithm with Spark

A Parallel Uncertain Frequent Itemset Mining Algorithm with ...

引用

IEEE International Conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Jiaman Ding Haibin Li Yuanyuan Wang Lianyin Jia Jinguo You Yang Yang Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China College of Engineering and Computer Science Australian National University Canberra Australia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

Frequent Itemset Mining (FIM) from large-scale databases has emerged as an important problem in the data mining and knowledge discovery research community. However, FIM suffers from three important limitations with the rapidly expanding of big data in all domains. First, it assumes that all items have the same importance. Second, it ignores the fact that data collected in a real-life environment is often inaccurate. Third, it is also a data-intensive and computation-intensive process which makes the FIM algorithm very time-consuming over large datasets. To address these issues, we propose a parallel uncertain frequent itemset mining algorithm with spark (Pufim). Pufim firstly expresses item uncertainty by considering both the probability and weight, and calculates the maximum probability weight value of 1-items. Next, a distributed Pufim-tree structure is designed inspiring by FP-Tree for reducing the times of scanning the databases. Each node of Pufim-tree stores an item and its maximum probability weight value. Finally, experiments on publicly available UCI datasets demonstrate that Pufim achieves more prominent results than other related approaches across various metrics. In addition, the empirical study also shows Pufim has a good scalability.

关键词： Itemsets Data mining Probability Database systems

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Research on Massive Video Image Processing based on Cloud Server

Research on Massive Video Image Processing based on Cloud Se...

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International Conference on Image, Vision and Computing (ICIVC)

作者： Yang Haigen Ding Qian Huang Yusheng Yu Longyan Xu Wenting Han Longbao Fu Xiao Guo Feng Engineering Research Center of Wider and Wireless Communication Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Beijing Institute of Mechanical and Electrical Engineering Beijing P.R. China China International Engineering Consulting Corporation Beijing P.R. China Nanjing University of Posts and Telecommunications Nanjing P.R. China

The following topics are dealt with: feature extraction; learning (artificial intelligence); convolutional neural nets; object detection; image segmentation; image classification; image colour analysis; computer visio... 详细信息

ISBN: (纸本)9781728123264

关键词： Massive video processing Intelligent video analysis distributed parallel computing Cloud computing Cloud Computing parallel PROCESSING (COMPUTERS) real-time analysis VIDEO IMAGES Clouds Videotapes server systems VIDEO ANALYSIS time series analysis

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Case Study on Design and Evaluation of a Multi-Soft-Core Processor

Case Study on Design and Evaluation of a Multi-Soft-Core Pro...

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International Conference and workshop on Computing and Communication (IEMCON)

作者： Michael Kirchhoff Lothar Wagner Bernd Däne Detlef Streitferdt Wolfgang Fengler Group for Computer Architecture and Embedded Systems Technische Universität Ilmenau Ilmenau Germany Group for Software Systems and Process Informatics Technische Universität Ilmenau Ilmenau Germany

ISBN: (纸本)9781728125312

Modern FPGAs (Field Programmable Gate Arrays) are becoming increasingly important when it comes to embedded system development. Within these FPGAs, soft-core processors are often used to solve a wide range of different tasks. Soft-core processors are a cost-effective and time-efficient way to realize embedded systems. The trend for soft-core processors, as well as mainstream CPUs (central processing units), leads to multi-core architectures. Both the necessary memory architectures and the compilers play an important role in this process. In this paper, a novel method that aims at minimizing the necessary memory resources on the FPGA while maximizing the processing speed of any given algorithm is described. In the first step, an application-specializable multi-soft-core processor architecture is presented that is capable of solving problems while adhering to hard real-time deadlines. Its special architecture and other necessary features are discussed. Furthermore, a method for the generation of optimized machine code for each processor core as well as hard real-time compatible deadlock handling mechanisms are presented. Selected algorithms are implemented to demonstrate the functionality and efficiency of the realized approach for different configurations of the multi-soft-core processor architecture.

关键词： Microprocessors Multicore processing Memory architecture Multiprocessor interconnection Field programmable gate arrays Field programmable gate arrays Memory architecture macroprocessor parallel processor interconnection PROCESSOR soft-core Processor Core embedded system development Processor Architectures Mechanical Code central processing units hard real-time

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Using DCT-based Approximate Communication to Improve MPI Performance in parallel Clusters

Using DCT-based Approximate Communication to Improve MPI Per...

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IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Qianqian Fan David J. Lilja Sachin S. Sapatnekar Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN

Communication overheads in distributed systems constitute a large fraction of the total execution time, and limit the scalability of applications running on these systems. We propose a DCT-based approximate communication scheme that takes advantage of the error resiliency of several widely-used applications, and improves communication efficiency by substantially reducing message lengths. Our scheme is implemented into the Message Passing Interface (MPI) library. When evaluated on several representative MPI applications on a real cluster system, it is seen that the fraction of total execution time devoted to communication reduces from 59% to 23%, even accounting for the computational overhead required for DCT encoding. For many communication-intensive applications, it is shown that our approximate communication scheme effectively speeds up the total execution time without much loss in quality of the result.

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Evaluation of Dynamic Task Scheduling Algorithms in a Runtime System for Heterogeneous Architectures 31

Evaluation of Dynamic Task Scheduling Algorithms in a Runtim...

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31st GI/ITG International Conference on Architecture of Computing systems, ARCS 2018

作者： Becker, Thomas Busse, Pablo Schuele, Tobias Karlsruhe Institute of Technology Karlsruhe76131 Germany Siemens AG Corporate Technology Munich81739 Germany

ISBN: (纸本)9783800745593

Heterogeneous parallel architectures present many challenges to application developers. One of the most important ones is the decision where to execute a specific task. As today's systems are often dynamic in nature, this cannot be solved at design time. A solution is offered by runtime systems that employ dynamic scheduling algorithms. Still, the question which algorithm to use remains. In this paper, we describe the integration of dynamic task scheduling algorithms well-known in the literature into EMB2, a library for parallel programming of embedded heterogeneous systems. Moreover, we evaluate these algorithms on a real system using different benchmarks. The evaluation covers different modes: In immediate mode, tasks are scheduled in the order they arrive in the system, whereas in batch mode, all ready-to-execute tasks are considered during the scheduling decision. Our experimental results show that batch mode heuristics generally obtain better results. An exception is the Minimum Completion time heuristic, which achieves similar results at less overhead and algorithm complexity. © ARCS 2018.

关键词： parallel programming

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ex-FTCD: A novel mapreduce model for distributed multi source shortest path problem

ex-FTCD: A novel mapreduce model for distributed multi sourc...

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3rd International Symposium on Signal Processing and Intelligent Recognition systems (SIRS)

作者： Gayathri, R. G. Nair, Jyothisha J. Amrita Vishwa Vidyapeetham Dept Comp Sci & Engn Amritapuri Tamil Nadu India

Computing the all pair shortest paths in a graph is a widely used solution, but a time-consuming process too. The popularly used conventional algorithms rely solely on the computing capability of the CPU, but fail to meet the demand of real-time processing and mostly do not scale well for larger data. In this paper, we propose the ex-FTCD (extending Full Transitive Closure with Dijkstra's) algorithm for finding the all pair shortest path by merging the features of the greedy technique in Dijkstra's single source shortest path method and the transitive closure property. Experiments show that the process improves computing speed and is more scalable. We re-designed the algorithm for the parallel execution and implemented it in mapreduce on Hadoop that supports the conventional map/reduce jobs. This work also includes the implementation on Spark that supports the in-memory computational capability which uses Random Access Memory for computations. The experiments show that the numbers of iterations are relatively small for even large networks.

关键词： All pair shortest path transitive closure distributed computing greedy approach

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Massive Finger-vein Identification based on Local Line Binary Pattern under parallel and distributed systems

Massive Finger-vein Identification based on Local Line Binar...

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Computer Science Society (SCCC) International Conference Chilean FLAGGED

作者： Ruber Hernández-García Sebastián Guidet Ricardo J. Barrientos Fernando Emmanuel Frati Laboratorio LITRP Facultad de Ciencias de la Ingeniería Universidad Católica del Maule Talca Chile Universidad Nacional de Chilecito Chilecito La Rioja Argentina

Massive individuals identification is a challenging problem in modern society. Particularly, finger-vein recognition is an emerging biometric technique with several advantages, especially in terms of security against forgery. In this paper, we propose a hybrid parallel matching process for finger-vein recognition under two different parallel platforms, by using the Local Line Binary Pattern descriptor and Hamming distance. Our proposal aims to reduce the computation time of the matching process for massive individuals identification by using finger-vein patterns. Extensive evaluation shows that our approach obtains a high speed-up under a multi-core platform and a close to linear behavior for a multi-node platform. The results with our hybrid parallel system show that it is suitable for real-time individuals identification, achieving a speed-up up to 129.98x. To the best of our knowledge, our work is the first implementation of finger-vein recognition under a parallel platform, which is the main contribution of this paper.

关键词： Silicon compounds Pattern matching Image segmentation Biometrics (access control) Security Forgery Hamming distance

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EdgeSys 2018 - Proceedings of the 1st ACM International workshop on Edge systems, Analytics and Networking, Part of MobiSys 2018

EdgeSys 2018 - Proceedings of the 1st ACM International Work...

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1st ACM International workshop on Edge systems, Analytics and Networking, EdgeSys 2018, held in conjunction with ACM MobiSys 2018

ISBN: (纸本)9781450358378

_oab The proceedings contain 9 papers. The topics discussed include: EdgeEye - an edge service framework for real-time intelligent video analytics;the web as a distributed computing platform;enabling GPU-assisted antivirus protection on android devices through edge offloading;a multi-cloudlet infrastructure for future smart cities: an empirical case study;profit-aware resource management for edge computing systems;Duvel: enabling context-driven, multi-profile apps on android through storage sand-boxing;enabling edge devices that learn from each other: cross modal training for activity recognition;semi-edge: from edge caching to hierarchical caching in network fog;and voice enabling mobile applications with UIVoice.

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Proceedings of the Annual ACM Symposium on Principles of distributed Computing

Proceedings of the Annual ACM Symposium on Principles of Dis...

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2018 workshop on Theory and Practice for Integrated Cloud, Fog and Edge Computing Paradigms, TOPIC 2018, in conjunction with the 37th ACM Symposium on Principles of distributed Computing, PODC 2018

ISBN: (纸本)9781450357760

The proceedings contain 7 papers. The topics discussed include: Relays: towards a link layer for robust and secure fog computing;distributing computations in fog architectures;scheduling at the edge for assisting cloud real-time systems;enabling exclusive shared access to cloud of things resources;digital epidemiology and beyond;a novel NFV schedule optimization approach with sensitivity to packets dropping positions;and GoEdge: a scalable and stateless local breakout method.

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parallel parameter optimization algorithm in dynamic general equilibrium models

Parallel parameter optimization algorithm in dynamic general...

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17th IFAC Technical-Committee-on-Optimal-Control (TC 2.4) workshop on Control Applications of Optimization (CAO)

作者： Gruzdev, Arseniy P. Melnikov, Nikolai B. Dalton, Michael G. Weitzel, Matthias O'Neill, Brian C. Lomonosov Moscow State Univ Moscow Russia RAS Cent Econ & Math Inst Moscow Russia NOAA Seattle WA USA European Commiss Joint Res Ctr Seville Spain Natl Ctr Atmospher Res POB 3000 Boulder CO 80307 USA

We present a parallel parameter optimization algorithm for reproducing future projections of certain model outputs in dynamic general equilibrium models. The optimization problem is reduced to a nonlinear system of equations. The Jacobian matrix for a Newton type solver in the problem is generated in parallel. The parameter optimization algorithm is implemented for parallel systems with distributed memory by using MPI. To achieve better performance of the parallel algorithm we use the parallel Fair-Taylor algorithm for computing an equilibrium path. Calculation of prices, input-output ratios and international trade for different time steps is carried out in parallel at each iteration of the method. The solution method is implemented for parallel systems with shared memory by using OpenMP. The effectiveness of the hybrid MPI+OpenMP parallel code for parameter optimization is demonstrated in the example of a global multi-sector energy economics model with scenarios that are used for studying climate change impacts on land use. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Computational general equilibrium model Economic growth Iterative methods parallel computing Energy economics Climate impacts

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